AIMC Topic: Odorants

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Analysis of the role of wind information for efficient chemical plume tracing based on optogenetic silkworm moth behavior.

Bioinspiration & biomimetics May 31, 2019
Many animals use olfactory information to search for feeding areas and other individuals in real time and with high efficiency. We focus on the chemical plume tracing (CPT) ability of male silkworm moths and investigate an efficient CPT strategy for ...
Algorithms Wind Odorants Moths Flight, Animal Optogenetics Animals Male Robotics Models, Biological
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Characterization of Key Aroma Compounds in a Commercial Rum and an Australian Red Wine by Means of a New Sensomics-Based Expert System (SEBES)-An Approach To Use Artificial Intelligence in Determining Food Odor Codes.

Journal of agricultural and food chemistry Mar 26, 2019
Although to date more than 10 000 volatile compounds have been characterized in foods, a literature survey has previously shown that only 226 aroma compounds, assigned as key food odorants (KFOs), have been identified to actively contribute to the ov...
Alcoholic Beverages Olfactometry Smell Chromatography, Gas Flavoring Agents Humans Artificial Intelligence Australia Wine Odorants Expert Systems Volatile Organic Compounds
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A predictive model for the evaluation of flavor attributes of raw and cooked beef based on sensor array analyses.

Food research international (Ottawa, Ont.) Mar 22, 2019
There are currently no standardized objective measures to evaluate beef flavor attributes, especially the comparison between raw beef and cooked beef. Beef flavor attribute is one of the most significant parameters for consumers. This study described...
Neural Networks, Computer Algorithms Young Adult Adult Humans Raw Foods Taste Cooking Food Preferences Red Meat Cluster Analysis Models, Statistical Odorants
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A neural data structure for novelty detection.

Proceedings of the National Academy of Sciences of the United States of America Dec 3, 2018
Novelty detection is a fundamental biological problem that organisms must solve to determine whether a given stimulus departs from those previously experienced. In computer science, this problem is solved efficiently using a data structure called a B...
Algorithms Animals Models, Biological Odorants Neural Networks, Computer Nerve Net Drosophila Olfactory Pathways
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Abstract concept learning in a simple neural network inspired by the insect brain.

PLoS computational biology Sep 17, 2018
The capacity to learn abstract concepts such as 'sameness' and 'difference' is considered a higher-order cognitive function, typically thought to be dependent on top-down neocortical processing. It is therefore surprising that honey bees apparantly h...
Behavior, Animal Mushroom Bodies Learning Animals Cognition Models, Neurological Odorants Probability Bees Machine Learning Software Brain Computer Simulation Neural Networks, Computer
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DeepLabCut: markerless pose estimation of user-defined body parts with deep learning.

Nature neuroscience Aug 20, 2018
Quantifying behavior is crucial for many applications in neuroscience. Videography provides easy methods for the observation and recording of animal behavior in diverse settings, yet extracting particular aspects of a behavior for further analysis ca...
Neural Networks, Computer Algorithms Animals Male Deep Learning Mice Posture Transfer, Psychology Mice, Inbred C57BL Behavior, Animal Humans Odorants Drosophila melanogaster Psychomotor Performance Nerve Net Video Recording Behavior
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Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis.

ACS sensors Aug 15, 2018
A sensing signal obtained by measuring an odor usually contains varied information that reflects an origin of the odor itself, while an effective approach is required to reasonably analyze informative data to derive the desired information. Herein, w...
Odorants Gases Machine Learning Water Nanoparticles Ethanol Silicon Dioxide Titanium Methanol
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Deep(er) Learning.

The Journal of neuroscience : the official journal of the Society for Neuroscience Jul 13, 2018
Animals successfully thrive in noisy environments with finite resources. The necessity to function with resource constraints has led evolution to design animal brains (and bodies) to be optimal in their use of computational power while being adaptabl...
Mushroom Bodies Olfactory Receptor Neurons Neuropil Reward Signal Detection, Psychological Odorants Conditioning, Operant Animals Afferent Pathways Synapses Reinforcement, Psychology Drosophila melanogaster Deep Learning Conditioning, Classical Signal-To-Noise Ratio Models, Neurological Avoidance Learning Association Learning Olfactory Perception Nerve Net Environment
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Predictive modeling for odor character of a chemical using machine learning combined with natural language processing.

PloS one Jun 14, 2018
Recent studies on machine learning technology have reported successful performances in some visual and auditory recognition tasks, while little has been reported in the field of olfaction. In this paper we report computational methods to predict the ...
Databases, Chemical Natural Language Processing Humans Odorants Machine Learning Taste Models, Theoretical Smell
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A Robot Equipped with a High-Speed LSPR Gas Sensor Module for Collecting Spatial Odor Information from On-Ground Invisible Odor Sources.

ACS sensors Jun 8, 2018
Improving the efficiency of detecting the spatial distribution of gas information with a mobile robot is a great challenge that requires rapid sample collection, which is basically determined by the speed of operation of gas sensors. The present work...
Surface Plasmon Resonance Particle Size Odorants Robotics Surface Properties Gases
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